Serum AZD7442 (tixagevimab–cilgavimab) concentrations and in vitro IC50 values predict SARS‐CoV‐2 neutralising antibody titres

Abstract Objectives The evolution of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) necessitates rapid methods for assessing monoclonal antibody (mAb) potency against emerging variants. Authentic virus neutralisation assays are considered the gold standard for measuring virus‐neutralising antibody (nAb) titres in serum. However, authentic virus‐based assays pose inherent practical challenges for measuring nAb titres against emerging SARS‐CoV‐2 variants (e.g. storing infectious viruses and testing at biosafety level‐3 facilities). Here, we demonstrate the utility of pseudovirus neutralisation assay data in conjunction with serum mAb concentrations to robustly predict nAb titres in serum. Methods SARS‐CoV‐2 nAb titres were determined via authentic‐ and lentiviral pseudovirus‐based neutralisation assays using serological data from three AZD7442 (tixagevimab–cilgavimab) studies: PROVENT (NCT04625725), TACKLE (NCT04723394) and a phase 1 dose‐ranging study (NCT04507256). AZD7442 serum concentrations were assessed using immunocapture. Serum‐based half‐maximal inhibitory concentration (IC50) values were derived from pseudovirus nAb titres and serum mAb concentrations, and compared with in vitro IC50 measurements. Results nAb titres measured via authentic‐ and lentiviral pseudovirus‐based neutralisation assays were strongly correlated for the ancestral SARS‐CoV‐2 virus and SARS‐CoV‐2 Alpha. Serum AZD7442 concentrations and pseudovirus nAb titres were strongly correlated for multiple SARS‐CoV‐2 variants with all Spearman correlation coefficients ≥ 0.78. Serum‐based IC50 values were similar to in vitro IC50 values for AZD7442, for ancestral SARS‐CoV‐2 and Alpha, Delta, Omicron BA.2 and Omicron BA.4/5 variants. Conclusions These data highlight that serum mAb concentrations and pseudovirus in vitro IC50 values can be used to rapidly predict nAb titres in serum for emerging and historical SARS‐CoV‐2 variants.


INTRODUCTION
][3][4] Monoclonal antibodies (mAbs), predominantly selected and developed for their neutralising potency against ancestral SARS-CoV-2, have played an important role in the prevention and treatment of COVID-19 in vulnerable populations, including immunocompromised individuals. 5,6][9][10] The neutralisation titres of COVID-19 mAbs in serum are often measured using authentic virus-based neutralisation assays (e.g. the plaque reduction neutralisation test [PRNT]), which are considered the gold standard for measuring antibody titres for many viral diseases. 11][13] The rapid evolution of SARS-CoV-2 has necessitated an equally rapid method for assessing the potency of mAbs against newly circulating variants, to determine whether existing mAbs will provide protection against emerging variants, particularly in individuals at high risk of COVID-19. 5,146][17][18][19] Such assays offer increased reproducibility and logistical advantages over authentic virus neutralisation assays. 11,12For example, the lentiviral pseudovirus neutralisation assay utilises a non-replicating, genetically modified lentiviral construct encoding the SARS-CoV-2 spike protein and a luciferase reporter gene. 12,132][13] Additionally, lentiviral pseudovirions can be consistently produced and rapidly adapted to new viral variants using public viral sequence data without the need to isolate infectious virus.Furthermore, COVID-19 mAb serum concentrations, normalised by neutralisation potency IC 50 values against different variants, can be used to estimate serum nAb titres, as described in Figure 1.These 'predicted nAb titres', calculated as serum mAb concentration divided by in vitro IC 50 , have been observed to correlate with protection against symptomatic SARS-CoV-2 infection. 20However, there remains a need to determine the degree of agreement between authentic virus and pseudovirus neutralisation assays, as well as to explore the reliability of using serum mAb concentration in combination with in vitro IC 50 values to predict nAb titres against emerging variants.AZD7442 (tixagevimab-cilgavimab) is composed of two extended half-life (M252Y/S254T/T256E [YTE]-modified) mAbs that bind to distinct non-overlapping epitopes on the SARS-CoV-2 spike receptor-binding domain, allowing for direct virus neutralisation. 21,22The AZD7442 mAb combination received emergency use authorisation (EUA) for COVID-19 pre-exposure prophylaxis in the United States in December 2021 and subsequently received authorisations for pre-exposure prophylaxis or treatment in the EU, Canada, Japan, Australia and other markets; however, with the emergence of resistant Omicron variants, the US EUA for AZD7442 was suspended in 2023. 23Despite this, throughout its development, AZD7442 safety, efficacy, pharmacokinetics (PK) and nAb titres to the ancestral SARS-CoV-2 virus have been characterised in clinical trials. 17,24,25Such findings include demonstration of AZD7442 efficacy in two phase 3 studies, in the prevention of symptomatic COVID-19 (PROVENT; NCT04625725) 17 and in the prevention of hospitalisation among outpatients with COVID-19 (TACKLE; NCT04723394). 25dditionally, AZD7442 has been shown to possess a range of in vitro IC 50 values against ancestral, Alpha, Delta and Omicron SARS-CoV-2 variants. 23,26Therefore, AZD7442 serum levels and nAb titres against different variants provide an ideal dataset to evaluate correlation between different neutralisation assay methods and correlation between mAb serum concentrations and variant-specific nAb titres, as well as for determining the utility of serum concentrations and in vitro IC 50 measurements to predict nAb titres.
Here, we first present an analysis of correlations between SARS-CoV-2 nAb titres measured by authentic-and pseudovirus-based neutralising assays using serological data from PROVENT, 17 TACKLE 25 and the phase 1 first-in-human study of AZD7442. 24Second, we use data from PROVENT to evaluate the relationship between serum AZD7442 concentrations and pseudovirus-derived nAb titres against multiple SARS-CoV-2 variants.

Correlation between authentic-and pseudovirus-based SARS-CoV-2 neutralisation assays
To better understand whether the pseudovirus-based SARS-CoV-2 neutralisation assays that were used to support the AZD7442 clinical development programme correlated with authentic virus-based neutralisation assays, we evaluated the correlation between nAb titres generated in the two assays, when measured in the same participants.The study designs for the PROVENT, TACKLE and phase 1 first-in-human studies are detailed in the Methods.Correlations between nAb titre levels (PRNT 80 for authentic virus assay and 50% infectious dose [ID 50 ] for pseudovirus assay; see the Methods) derived from authentic-and pseudovirus-based neutralising assays were evaluated using serum samples obtained from study participants (Figure 2; Table 1). 27 strong correlation (defined as Spearman correlation coefficient ≥ 0.7) was observed between nAb titres against ancestral SARS-CoV-2 D614G authentic virus and ancestral SARS-CoV-2 pseudovirus in PROVENT study participants (Spearman correlation coefficient: 0.78 [95% confidence interval [CI] 0.75-0.81])(Figure 2a).The dataset included matched samples obtained throughout the course of the study (Days 29, 58 and 183).An analysis in TACKLE study participants (Days 6, 15 and 29) also revealed a strong correlation between ancestral SARS-CoV-2 D614G authentic and ancestral SARS-CoV-2 pseudovirus nAb titres (Spearman correlation coefficient: 0.70 [95% CI 0.66-0.74])(Figure 2b).An important distinction between the PROVENT and TACKLE studies was the timing of AZD7442 administration; the PROVENT study evaluated AZD7442 300 mg via intramuscular (IM) injection for pre-exposure prophylaxis, whereas the TACKLE study examined AZD7442 600 mg IM as an outpatient treatment after a confirmed SARS-CoV-2 infection.In this context, our data from TACKLE participants illustrate that a strong correlation between authentic and pseudovirus nAb titres is maintained over time in the outpatient treatment setting, despite the likely presence of nAbs from participant immune responses following SARS-CoV-2 infection and from AZD7442.
We also evaluated authentic and pseudovirus nAb titres for SARS-CoV-2 Alpha to expand the correlation analysis to another SARS-CoV-2 variant.Analysis of samples from the AZD7442 phase 1 first-in-human study participants showed a strong correlation between authentic and pseudovirus nAb titres (Spearman correlation coefficient: 0.93 [95% CI 0.91-0.95])(Figure 2c).These samples came from healthy participants who received AZD7442 300 mg IM, 300 mg intravenous (IV), 1000 mg IV or 3000 mg IV, and therefore, the range of serum AZD7442 concentrations was broader than in the phase 3 studies.The dataset included matched samples obtained throughout the course of the study ( Days 8, 31, 61, 91, 151, 211, 271 and 361).The correlation remained consistent across the range of serum AZD7442 concentrations and collection times following dosing.
As expected, we observed a fold difference between authentic and pseudovirus assays (ranging from 9-fold to 20-fold across the three groups), which is likely a result of differences between assay outputs (PRNT 80 and ID 50 ) and setup (e.g.viral replication and growth kinetics).However, Spearman correlation coefficients were ≥ 0.7 in each of these analyses despite the different clinical settings (i.e.pre-exposure prophylaxis and post-infection treatment), and across various doses of AZD7442 (Table 1).Taken together, these data provide strong evidence that authentic-and pseudovirus-derived nAb titres correlate and are equally suitable for assessing nAb titres across study populations.

Correlations between serum AZD7442 concentrations and pseudovirus-derived nAb titres across SARS-CoV-2 variants in PROVENT study participants
To explore the relationship between serum AZD7442 concentration and nAb titres, we used a subset of matched samples from approximately 300 PROVENT study participants with pseudovirus nAb titres against ancestral SARS-CoV-2, as well as five later variants (Figure 3).A linear relationship was observed between serum AZD7442 concentrations and pseudovirus nAb titres, with Spearman correlation coefficients ≥ 0.78, illustrating a strong correlation between serum AZD7442 concentrations and reported nAb titres across multiple SARS-CoV-2 variants (Table 2).Serum AZD7442 concentrations and pseudovirus nAb titres displayed similar correlations and patterns of variability over time for ancestral SARS-CoV-2, as for the Alpha, Delta, Omicron BA.2 and Omicron BA.4/5 variants (Supplementary figure 1).Serum AZD7442 concentration-nAb titre pairs with a measurement below the lower limit of quantification (LLoQ) for the PK assay and nAb assay were excluded from this analysis, as measurements without a quantifiable result cannot inform the numerical relationship between   The correlation coefficient estimate for the repeated measurement data is calculated following the methods by Hamlett et al., 46 and the 95% CI for the correlation coefficient was estimated using the normal approximation method by Shen and Lu. 47hese two metrics (e.g.serum-based IC 50 ).However, a strong rank-based correlation (Spearman correlation coefficients > 0.70) was maintained even when samples below the LLoQ were imputed to 1/2 the LLoQ (Supplementary table 1).For Omicron BA.1, as most observations were below the LLoQ in the pseudovirus nAb assay, it was deemed there was not sufficient data to evaluate the correlation for this variant.As expected, because of decreasing levels of AZD7442 over time, the proportion of samples with nAb titres below the LLoQ of the neutralisation assay increased at Day 183 for both Omicron BA.2 and BA.4/5, when nAb titres were generally lower than those for the ancestral, Alpha and Delta variants, which is consistent with the established potency of AZD7442 against these variants.results show a consistent relationship between predicted and observed nAb titres across SARS-CoV-2 variants (Figure 3b), suggesting that serum mAb concentrations and in vitro neutralisation IC 50 measurements can effectively estimate, or predict, post-administration nAb titres.Notably, a small number of data points fell to the left of the diagonal line in Figure 3b, suggesting that these participants may have had an asymptomatic SARS-CoV-2 infection or received a COVID-19 vaccine, resulting in higher than expected nAb titres.

DISCUSSION
Neutralising mAbs have played a significant role in both the prevention of, and treatment against, COVID-19. 17,25Although at the time of manuscript preparation AZD7442 is no longer authorised for COVID-19 pre-exposure prophylaxis in the United States, the neutralising activity of AZD7442 has been extensively examined throughout its history of use. 23,26The use of antibody half-life extension technologies such as the YTE and LS modifications have made long-acting antibodies (LAABs) attractive options for pre-exposure prophylaxis in populations who are unable to mount a sufficient immune response, such as those with immunocompromising conditions, transplant recipients and those taking powerful immunosuppressants. 17,25,28,29As both prophylactic and treatment approaches for COVID-19 rely inherently on the susceptibility of the SARS-CoV-2 virus to mAb neutralisation, it is important to have the ability to rapidly assess the neutralising potency of COVID-19 mAbs against emerging viral variants.
The data presented herein support the use of pseudovirus-derived nAb titres as a surrogate for authentic-derived titres as a measurement of viral neutralisation in a clinical setting.This alternative approach presents an important opportunity for rapid development and assessment of mAbs targeting SARS-CoV-2, compared with the use of authentic virus-based neutralisation assays, which present practical challenges in their development, validation and implementation against rapidly emerging SARS-CoV-2 variants.While potential differences in viral growth kinetics 30 pose a challenge for any cross-variant comparisons of authentic virus assays, lentiviral SARS-CoV-2 pseudoviruses are identical, with the exception of the spike sequence, across different variants; they are therefore more likely to have consistent assay parameters across variants.It is, however, important to note that the same type of assay and the same laboratory and/or vendor should be used for cross-variant comparisons, because of differences in the numerical titre measurements with different assays.
In this report, we also demonstrate the suitability of predicted nAb titres as a surrogate for the assessment of serum neutralisation through a combination of robust correlation between serum AZD7442 concentrations and pseudovirus nAb titres from matched samples across five SARS-CoV-2 variants, and consistency of the associated serum-based IC 50 with in vitro AZD7442 IC 50 values across a wide range of potencies (pseudovirus IC 50 values of  [11][12][13] Therefore, estimating nAb titres based on mAb serum concentration in conjunction with in vitro IC 50 values provides both a fast and 'clean' estimate of nAb levels related specifically to drug administration.This is key in facilitating rapid immunobridging studies by enabling enrolment of participants with varying levels of nAbs at baseline (i.e. both healthy and immunocompromised participants), allowing for faster recruitment and smaller required sample sizes.
Similar findings have been shown in the human immunodeficiency virus (HIV) field; there is a precedent for the use of serum drug concentrations normalised by IC 50 to estimate nAb titres (referred to as the 'inhibitory quotient') for therapeutic drug monitoring. 31,32Furthermore, an analysis of the broadly neutralising anti-HIV envelope glycoprotein mAb, VRC01, illustrated that predicted nAb titres (calculated as VRC01 serum concentration/in vitro IC 50 ) were comparable with measured titres for several HIV strains. 33,34The suitability of predicted nAb titres as a surrogate for measured nAb titres across multiple variants, as demonstrated in this report, in turn supports the use of a predicted nAb endpoint to facilitate effective comparisons of nAb titres across variants for which the baseline nAb levels are expected to be different, because of differences in vaccine antigens and variant exposure (e.g.ancestral SARS-CoV-2 and contemporary Omicron subvariants). 35,36Such cross-variant comparisons would enable immunobridging studies to rapidly compare nAb titres associated with efficacy demonstrated against ancestral variants to neutralising titres against currently circulating variants of concern, either within a randomised clinical trial, or between new clinical trial data and historical data from past efficacy trials.
Predicted nAb titres could also facilitate definition of a nAb-based correlate of protection for mAbs targeting SARS-CoV-2, which does not currently exist.Predicted nAb titres can be estimated over time using population-PK model predictions and across variants for which nAb titres have not been measured in clinical samples, allowing for continuous assessment of titres through all SARS-CoV-2 variant waves. The utilisation of serum concentrations in combination with in vitro IC 50 values also allows for the prediction of nAb titres in new populations and scenarios.The effects of individual participants and disease characteristics on mAb serum concentrations and variability have been extensively characterised across different populations and indications in population-PK models built upon pooled clinical data.39 As such, population-PK model predictions and in vitro neutralisation data could be used together to assess predicted nAb titres for different dosing regimens in target populations and indications more quickly than clinical studies can be developed and executed.39-41 Such a strategy would allow for continuous review of whether current and future mAb therapeutics would be likely to maintain protection against newly emergent SARS-CoV-2 variants, particularly in vulnerable populations.
There are two limitations of this analysis that may limit the generalisability of the presented results.First, the current study was limited to a single mAb combination, AZD7442.Second, this dataset was collected prior to widespread availability of COVID-19 vaccines, and therefore does not assess the impact of vaccine-induced or naturally elicited nAb titres on the relationship between serum concentrations and nAb titres.These limitations can be addressed in future analyses of similar data from other SARS-CoV-2targeting mAbs.An additional technical limitation is the assumption of a Hill coefficient of 1 for the

Study participants
The PROVENT study (NCT04625725) was conducted between November 2020 and November 2023.This double-blind, placebo-controlled phase 3 trial assessed the safety, immunogenicity and efficacy of a single dose of AZD7442 as pre-exposure prophylaxis against COVID-19 in individuals aged ≥ 18 years who were at increased risk of an inadequate response to COVID-19 vaccination or had an increased risk of exposure to SARS-CoV-2. 17Participants were required to be negative for SARS-CoV-2 via serological testing and to be vaccine naı ¨ve.A total of 5973 participants were enrolled from 87 sites in Belgium, France, Spain, the UK and the United States, and 5197 participants were randomised in a 2:1 ratio to AZD7442 or placebo.
The TACKLE study (NCT04723394) was conducted between January 2021 and October 2022.This doubleblind, placebo-controlled phase 3 trial assessed the safety and efficacy of AZD7442 for preventing progression to severe disease or death in non-hospitalised participants aged ≥ 18 years with mild-to-moderate COVID-19. 25articipants required a reverse transcription polymerase chain reaction (RT-PCR) or antigen test-confirmed SARS-CoV-2 infection and a World Health Organization Clinical Progression Scale score of > 1 to < 4, were vaccine naı ¨ve, and had to receive AZD7442 within 7 days from selfreported onset of symptoms.The trial enrolled 1014 participants from 95 sites in the United States, Latin America, Europe and Japan, with 910 being randomised in a 1:1 ratio to AZD7442 or placebo.
The AZD7442 phase 1 first-in-human (NCT04507256) dose-escalation study was conducted between August 2020 and October 2021.Full eligibility criteria have been previously described. 24Briefly, study participants were aged 18-55 years at the time of screening, were negative for SARS-CoV-2 via quantitative RT-PCR and/or serological testing before randomisation, and were considered healthy by medical history, physical examination and baseline safety laboratory studies, according to the judgement of the investigator.

Study approval
The PROVENT, TACKLE and AZD7442 phase 1 first-in-human study protocols and amendments were approved by the ethics committee or institutional review board at each participating centre.The final version of the study protocols and statistical analysis plans have been published previously and can be accessed as part of Levin et al. (2022), 17 Montgomery et al. (2022) 25 and Forte-Soto et al. (2023), 24 respectively.The studies were all conducted in accordance with the principles of the Declaration of Helsinki and the International Council for Harmonization Good Clinical Practice guidelines.All participants in all studies provided written informed consent before enrolment.

Study design
The PROVENT, TACKLE and AZD7442 phase 1 first-in-human studies have been previously described. 17,24,25Briefly, in the PROVENT study, participants aged ≥ 18 years who were at risk of inadequate response to COVID-19 vaccination and/or had an increased risk of exposure to SARS-CoV-2 were randomised 2:1 to receive AZD7442 300 mg (comprising two consecutive IM injections of tixagevimab 150 mg and cilgavimab 150 mg) or matched saline placebo.In February 2022, the US Food and Drug Administration recommended an increase in the dose of AZD7442 to 600 mg (tixagevimab 300 mg and cilgavimab 300 mg) because of the emergence of Omicron BA.1.Primary endpoints were the first episode of symptomatic COVID-19 after exposure to AZD7442 or placebo, and safety. 17In the TACKLE study, unvaccinated, non-hospitalised participants aged ≥ 18 years with mild-tomoderate COVID-19 were randomised 1:1 to be dosed within 7 days of symptom onset with AZD7442 600 mg or matched saline placebo.Primary endpoints were all-causality severe COVID-19 or death up to Day 29, and safety throughout the course of the study. 25In the AZD7442 phase 1 first-in-human study, healthy adults aged 18-55 years were randomised 5:1 to receive a single dose of IM AZD7442 300 mg or IV AZD7442 300 mg, 1000 mg or In vitro IC 50 values predict SARS-CoV-2 nAb titres LE Clegg et al.
3000 mg.AZD7442 comprised tixagevimab and cilgavimab in a 1:1 ratio for each formulation.The primary endpoint was safety and tolerability. 24

Sample collection
For the analyses herein, samples were derived from the PROVENT, TACKLE and AZD7442 phase 1 first-in-human studies. 17,24,25In the AZD7442

Pharmacokinetic assessments
Bioanalytical analyses of tixagevimab and cilgavimab in serum were performed by PPD Laboratories (Richmond, VA, USA), using immunocapture to the SARS-CoV-2 receptor-binding domain followed by denaturation and detection of AZD7442-specific peptides by liquid chromatography-mass spectrometry as described by Mu et al. (2022), 42 which was validated in accordance with relevant regulatory guidelines.

Authentic virus neutralisation assay
Serum-neutralising titres were evaluated using the SARS-CoV-2 PRNT (Viroclinics Biosciences, Rotterdam, Netherlands).As described previously, 22 a standard number of SARS-CoV-2 infectious units were preincubated with serial dilutions of serum for 1 h.The virus/serum mixtures were subsequently added to confluent Vero E6 cell monolayers (American Type Culture Collection, Manassas, VA, USA).After 16-24 h, cells were formalin-fixed and then incubated with a mAb targeting the SARS-CoV-2 nucleocapsid protein, followed by a secondary anti-human immunoglobulin G horseradish peroxidase conjugate (Thermo Fisher Scientific, Waltham, MA, USA) and KPL TrueBlue substrate (SeraCare Life Sciences Inc., Milford, CT, USA).The immunostained plates were scanned using an ImmunoSpot analyzer (Cellular Technology Limited, Cleveland, OH, USA), equipped with software for the quantification of nucleocapsid-positive cells.SARS-CoV-2 neutralisation titres (defined by PRNT 80 , or the dilution of a sample that produced a 80% reduction in virus) were calculated from these spot counts as described by Zielinska  et al. (2005). 43

Statistical analyses
To determine the level of correlation between SARS-CoV-2 nAb titres derived from authentic virus and pseudovirus neutralisation assays, as well as between serum concentrations and observed nAb titres, post hoc correlation analyses were performed using serological data collected from the PROVENT, TACKLE and/or AZD7442 phase 1 first-in-human studies.To account for skewing, log 10 -transformed values were considered.Bias-adjusted Spearman's rank correlation estimates were used to determine the strength of the relationships, with Fisher's Z transformation used to derive 95% CIs.A repeated measures correlation was also performed as a sensitivity analysis for authentic virus and pseudovirus neutralisation assays, as reported in Table 1, for groups where measurements from both assays were available.This was calculated following the methods by Hamlett et al., 46 and the 95% CI for the correlation coefficient was estimated using the normal approximation method by Shen and Lu. 47Details are given in the subsection below for the interested reader.

Derivation for repeated measures correlation between pseudovirus-based and authentic virus nAb titres
For this analysis, Hamlett's linear mixed model 46 was fitted using data from participants i from the relevant studies, at visits j using available post-baseline measurements, with response k for either the log 10 -transformed authentic virus nAb titres (R 1 ) or log 10 -transformed pseudovirus-based nAb titres (R 2 ).Covariates include an intercept and the type of response, where a value of 0 and 1 is assigned if the response variable is either R 1 or R 2 , respectively.A random effect for type of response was fit at the participant level with unstructured covariance.A repeated effect was also fit for the type of response for visits nested within participant level with an unstructured covariance, to model the residual errors.The Kenward-Roger degrees of freedom method was used, and maximum likelihood estimation was performed.
The variance of the random effect has the form The residual variance has the form , where m i is the number of observations for participant i.
The repeated measures correlation (b ρÞ was derived as follows: Applying the delta method, the partial derivative vector of b ρ is defined as follows: where The 95% CI was derived as follows: where Σ is the asymptotic covariance from the linear mixed model.

Calculation of fold difference for pseudovirus and authentic virus nAb assays
In Figure 2, estimated fold difference values were calculated from nAb titres for pseudovirus and authentic virus assays, and simple linear regression lines are presented for visualisation.A normally distributed generalised linear mixed effect model was fitted for each participant i and timepoint j, using the form where Y i,j = log 10 pseudovirus nAb titre i,j À Á ; μ i,j = β 0 þ log 10 authentic virus neutralising titre i,j À Á ; G random participant unstructured covariance matrix.
The 1:1 relationship (linear slope = 1) was assumed to evaluate the overall fold difference between the two methods.From this model, the fold difference was derived as 10 β 0 , with the same transformation applied to the 95% confidence limits of β 0 to derive the 95% CI.

Calculation of serum-based IC 50 values
To estimate serum-based AZD7442 IC 50 values from serum mAb concentrations and observed nAb titre data for variant k, the assumed relationship to fit is nAb titre k = Serum concentration ng mL -1 À Á IC 50k ng mL -1 À Á : This model form assumes a Hill coefficient of 1 for each variant, in order to allow the calculation of predicted nAb titres based on serum concentrations and in vitro IC 50 values alone.Using a more complex relationship between serum concentration and pseudovirus nAb (including the exponential term that would correspond to the slope on the log-log scale) would necessitate the collection of observed nAb data for each variant to fit the relationship in the future.
We expect residuals for nAb titres and serum concentration to be log-normally distributed.Therefore, to model this we consider the form: A normally distributed generalised linear mixed effect model was fitted for each participant i, timepoint j, and variant k using the form: where Y i,j,k = log 10 nAb titre i,j,k À Á ; μ i,j,k = β k þ log 10 ðSerum concentration crbigð ng mL -1 Â Ã i,j crbigÞÞ; G random participant unstructured covariance matrix.
From this model, Given this is a monotonic transformation, the 95% CI can be derived from back transformation.The same back transformation was applied to the confidence limits of β k to derive the 95% CI.
In Figure 3a and Supplementary figures 1 and 2a, the predicted nAb titre line is plotted using serum AZD7442 concentrations and predicted nAb titres.In Figure 3b and Supplementary figure 2b, the line y = x is plotted to compare agreement between the observed and predicted nAb titres.All PK and nAb titre measurements below the LLoQ were imputed to half of the LLoQ for visualisation but were excluded in correlation analyses, unless specified.

Figure 1 .
Figure 1.Calculation of predicted nAb titres.This schematic illustrates how in vitro IC 50 values and serum mAb concentrations can be used to predict nAb titres if measured using the same pseudovirus neutralisation assay.IC 50 , half-maximal inhibitory concentration; mAb, monoclonal antibody; nAb, neutralising antibody; SARS-CoV-2, severe acute respiratory coronavirus 2.

Figure 3 .
Figure 3. Correlation between AZD7442 serum concentrations and SARS-CoV-2 pseudovirus nAb titres in PROVENT.Post hoc correlation analysis depicting the relationship between nAb titres determined by (a) pseudovirus assay and serum concentrations of AZD7442; or (b) predicted nAb titres.Data points depict matched PK and nAb sample pairs (observations) from the same PROVENT study participants.Colours indicate different SARS-CoV-2 variants.PK and nAb titre measurements below the LLoQ were imputed to half of the LLoQ for visualisation in (a).LLoQ, lower limit of quantification; nAb, neutralising antibody; PK, pharmacokinetic.

Table 1 .
Correlations between authentic versus pseudovirus-based nAb titres in serum samples from AZD7442 clinical studies AZD7442 trial Authentic SARS-CoV-2 virus n a Spearman correlation b (95% CI) Repeated measures correlation c (95% CI) interval; LLoQ, lower limit of quantification; nAb, neutralising antibody; SARS-CoV-2, severe acute respiratory coronavirus 2. a Number of available post-baseline observations above LLoQ for both authentic virus and pseudovirus nAb titres.b As log 10 -transformed nAbs are skewed, the bias-adjusted Spearman correlation was used following Fisher's Z transformation for the 95% CI. c

ª
2024 The Author(s).Clinical & Translational Immunology published by John Wiley & Sons Australia, Ltd on behalf of Australian and New Zealand Society for Immunology, Inc.
Third, we evaluate whether serum-derived IC 50 values are similar to in vitro IC 50 measurements.Finally, we use serum concentrations and in vitro IC 50 measurements to predict nAb titres and compare these to measured nAb titres across five SARS-CoV-2 variants.

Table 2 .
23,26IC 50 , to observed nAb titres against the ancestral virus and the Alpha, Delta and Omicron BA.1, BA.2 and BA.4/5 variants.The Spearman correlations for serum AZD7442 concentrations and pseudovirus nAb titres across SARS-CoV-2 variants in PROVENT b As log 10 -transformed nAbs and serum concentrations are skewed, the bias-adjusted Spearman correlation was used following Fisher's Z transformation for the 95% CI. c As a high percentage of observations were below the LLoQ for Omicron BA.1, it was deemed there were not sufficient data to evaluate the serum concentration and nAb correlation.ª 2024 The Author(s).Clinical & Translational Immunology published by John Wiley & Sons Australia, Ltd on behalf of Australian and New Zealand Society for Immunology, Inc.

Table 3 .
Comparison between serum-based and in vitro AZD7442 IC 50 values for ancestral SARS-CoV-2 and SARS-CoV-2 variants SARS-CoV-2 virus n a Serum-based AZD7442 IC 50 value, ng mL À1 (95% CI) b In vitro AZD7442 IC 50 value, ng mL À1 (STD) c Number of available post-baseline observations above the LLoQ for both pseudovirus nAb titres and serum concentration for calculation of serum-based AZD7442 IC 50 values.Serum-based AZD7442 IC 50 values were calculated as detailed in Statistical analyses: Derivation of serum-based IC 50 values.As a high percentage of observations were below the LLoQ for Omicron BA.1, it was deemed there was not sufficient data to evaluate the IC 50 and correlation.
a b c STD was based on estimated assay precision from two technical replicates.d The results here support the consistency of the serum-based IC 50 values with in vitro values, as well as predicted nAb titres with observed pseudovirus nAb titres under this set of assumptions, and confirm the utility of the presented approach to quickly estimate clinical nAb titres for new mAbs and new SARS-CoV-2 variants.
ª 2024 The Author(s).Clinical & Translational Immunology published by John Wiley & Sons Australia, Ltd on behalf of Australian and New Zealand Society for Immunology, Inc.